1. Field of Art
The present disclosure generally relates to the field of digital image processing, and more specifically, to methods of removing haze from images.
2. Description of Related Art
When a photograph is taken of a scene in which haze or fog is present in the atmosphere, it degrades the content of the resulting image. The color of the objects in the scene are blended with light reflected from the atmosphere. Such blending is more severe when the object is further away from the camera.
To counter the effects of haze, several de-hazing methods have been proposed to improve image quality. One class of techniques relies on enhancing the contrast of an image, example of which are described in “Single Image Dehazing Based on Contrast Enhancement” by Jin-Hwan Kim, Jae-Young Sim, and Chang-Su Kim, IEEE International Conference on Acoustics, Speech and Signal Processing, May 2011. Such techniques are computationally intensive and typically take on the order of 10 seconds to complete. Another class of techniques relies on a dark channel prior, an example of which is described in “Single Image Haze Removal Using Dark Channel Prior” by Kaiming He, Jian Sun, and Xiaoou Tang, IEEE Conference on Computer Vision and Pattern Recognition, June 2009. In this example, a dark channel prior is proposed to remove haze from a single input image. Observing that most local patches in haze-free outdoor images contain some pixels having very low intensities in at least one color channel, a dark channel prior is used with a haze imaging model to estimate the thickness of the haze.